Improved CEEMD-based correction method for low-frequency shock response spectrum in large dual-wave shock tester devices

The shock response spectrum (SRS), calculated from a shock acceleration signal, is a critical indicator of shock environments. However, under intense loads, acceleration sensors are prone to trend term errors that can cause significant drift in the low-frequency spectral lines of large dual-wave shock tester devices. To address this issue, the complementary ensemble empirical mode decomposition (CEEMD) method was employed to decompose acceleration signals and restore the actual shock environment. Intrinsic mode functions (IMFs) were cross-correlated and compared to a predefined threshold to identify the effective IMF components required to reconstruct the signal. K-means clustering was employed to further validate the effectiveness of the IMFs for enhanced selection accuracy. Finally, the reconstructed acceleration signal was used to calculate a corrected SRS. The proposed approach demonstrated significant improvements over the traditional CEEMD algorithm. The corrected SRS exhibits a 5.6316 dB/oct slope in the low-frequency band, reflecting an equal displacement trend. The maximum error at the corresponding frequency was less than 6 % in comparison to the relative displacement response measured by low-frequency spring oscillators. This improved CEEMD correction method can effectively restore the actual shock environment of a dual-wave shock tester device, offering a valuable reference for evaluating shock resistance in onboard equipment.